Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented image processing method, comprising: receiving, by a computer processor, a first lookup table representing a pixel-to-pixel mapping of source pixel coordinates of an input image to destination pixel coordinates of an output image; generating, by the computer processor, a second lookup table representing a vector-to-pixel mapping of a first plurality of vectors of the destination pixel coordinates to a first plurality of the source pixel coordinates based on the first lookup table; receiving, by the computer processor, source image data; and applying, by the computer processor, a linear remapping operation from the source image data to each of the destination pixel coordinates in the first plurality of vectors in the second lookup table to obtain a first portion of destination image data.
This invention relates to image processing techniques for efficient pixel remapping. The problem addressed is the computational cost of directly applying pixel-to-pixel mappings in image transformations, which can be resource-intensive for large images or complex transformations. The solution involves optimizing the remapping process by leveraging vector-based operations. The method begins by receiving a first lookup table that defines a direct pixel-to-pixel mapping between source and destination coordinates. This table specifies how each pixel in the input image should be positioned in the output image. Next, a second lookup table is generated, which maps groups of destination pixel coordinates (vectors) to corresponding source pixel coordinates. This second table enables batch processing of multiple pixels at once, reducing the number of individual operations needed. The system then receives the source image data and applies a linear remapping operation. This operation uses the second lookup table to efficiently transform the source image data into the desired output format. By processing multiple pixels in vectors rather than individually, the method significantly improves computational efficiency while maintaining accuracy in the transformation process. This approach is particularly useful in applications requiring real-time image processing or handling high-resolution images.
2. The method of claim 1 , wherein all of the destination pixel coordinates in each of the first plurality of vectors correspond to pixel-to-pixel mappings in the first lookup table that are linear with slope 1 with respect to each other.
This invention relates to image processing techniques for generating high-quality images from low-resolution input data. The method addresses the challenge of accurately mapping pixel coordinates between different image resolutions or formats, particularly when preserving geometric relationships and avoiding distortion. The method involves using a first lookup table to store pixel-to-pixel mappings between source and destination coordinates. These mappings are constrained such that all destination pixel coordinates in each of the first plurality of vectors correspond to linear relationships with a slope of 1. This ensures that the mappings maintain a consistent, one-to-one correspondence between source and destination pixels, preventing distortion or misalignment in the output image. Additionally, the method may include generating a second lookup table for additional pixel mappings, where these mappings are derived from the first lookup table but may include non-linear transformations. The second lookup table allows for more complex adjustments while still referencing the initial linear mappings to maintain overall image integrity. The technique is particularly useful in applications requiring precise image scaling, format conversion, or interpolation, where maintaining geometric accuracy is critical. By enforcing linear relationships in the primary mappings, the method ensures that the output image retains the intended structure and avoids artifacts caused by non-linear distortions.
3. The method of claim 1 , wherein the linear remapping operation comprises retrieving, by the computer processor and from the source image data, first source pixel data corresponding to a respective one of the first plurality of vectors in the second lookup table based on the vector-to-pixel mapping in the second lookup table.
This invention relates to image processing techniques for linear remapping operations in computer graphics. The problem addressed is efficiently transforming source image data into a target representation using vector-based remapping, particularly in applications like texture mapping, image warping, or real-time rendering where performance and accuracy are critical. The method involves a two-step process. First, a second lookup table is generated, where each entry in this table maps a vector to a corresponding pixel in the source image data. This table is constructed based on a predefined vector-to-pixel relationship, ensuring that each vector in the table can be traced back to a specific pixel in the source image. During the remapping operation, the system retrieves source pixel data from the original image by using the vectors stored in the second lookup table. Specifically, for each vector in the table, the corresponding pixel data is fetched from the source image according to the vector-to-pixel mapping defined in the table. This allows the system to efficiently access the necessary pixel data for further processing, such as interpolation or transformation, without repeatedly recalculating the mapping for each vector. The approach optimizes performance by leveraging precomputed mappings, reducing computational overhead in applications requiring frequent or real-time image transformations. The method is particularly useful in scenarios where source image data must be dynamically remapped to different target representations while maintaining high fidelity and low latency.
4. The method of claim 3 , further comprising performing, by the computer processor, an interpolation on the first source pixel data to obtain the first portion of the destination image data.
This invention relates to image processing techniques for generating high-resolution images from lower-resolution source data. The problem addressed is the need to accurately reconstruct or upscale images while preserving detail and minimizing artifacts, particularly when working with limited source information. The method involves processing source pixel data to produce a destination image with improved resolution. A key step is performing interpolation on the source pixel data to generate a portion of the destination image. This interpolation step is applied to the first set of source pixel data to derive the corresponding portion of the destination image data. The interpolation may use various techniques, such as linear, polynomial, or spline-based methods, to estimate pixel values in the destination image where direct source data is unavailable. The method may also include additional steps, such as filtering the source pixel data to reduce noise or enhance edges before interpolation. The interpolation process ensures that the destination image maintains visual coherence and avoids distortions that can occur during simple scaling operations. The technique is particularly useful in applications like medical imaging, satellite imagery, and digital photography, where high-resolution output is desired from lower-resolution inputs. The approach balances computational efficiency with image quality, making it suitable for real-time or near-real-time processing.
5. The method of claim 1 , further comprising generating a third lookup table representing a listing of a second plurality of vectors of the destination pixel coordinates.
A system and method for image processing involves generating lookup tables to optimize the transformation of pixel coordinates between source and destination images. The method addresses the computational inefficiency of real-time image transformations, such as those required in medical imaging, satellite imaging, or augmented reality, where precise and rapid coordinate mapping is essential. The invention generates a first lookup table containing a plurality of vectors representing source pixel coordinates and a second lookup table containing a plurality of vectors representing destination pixel coordinates. These tables enable efficient mapping between source and destination pixels, reducing the need for repeated calculations during image rendering. Additionally, the method generates a third lookup table that further refines the mapping by listing a second plurality of vectors of the destination pixel coordinates, enhancing accuracy and performance. The lookup tables are precomputed and stored, allowing for fast retrieval and application during image processing, thereby improving real-time performance and reducing computational overhead. This approach is particularly useful in applications where high-speed, low-latency image transformations are required.
6. The method of claim 5 , wherein at least one of the destination pixel coordinates in each of the second plurality of vectors correspond to a pixel-to-pixel mapping in the first lookup table that is not linear with slope 1 with respect to other pixel-to-pixel mappings.
This invention relates to image processing techniques, specifically methods for generating and using lookup tables to map pixel coordinates in image transformations. The problem addressed involves the need for efficient and flexible pixel-to-pixel mappings that can handle non-linear transformations while maintaining computational efficiency. The method involves generating a first lookup table that defines pixel-to-pixel mappings between input and output images. This table includes a plurality of vectors, each representing a mapping from an input pixel coordinate to an output pixel coordinate. The key innovation is that at least one of the destination pixel coordinates in a second plurality of vectors within this table corresponds to a non-linear mapping with respect to other mappings in the table. This non-linearity means that the slope of the mapping is not equal to 1, allowing for more complex transformations such as warping, distortion correction, or other non-uniform adjustments. The method ensures that the lookup table can accommodate both linear and non-linear mappings, providing flexibility in image processing tasks where different regions of an image may require different types of transformations. This approach optimizes computational efficiency by precomputing the mappings and storing them in a lookup table, reducing the need for real-time calculations during image processing. The technique is particularly useful in applications like image warping, lens distortion correction, and other scenarios where precise control over pixel placement is required.
7. The method of claim 5 , further comprising applying a non-linear remapping operation from the source image data to each of the destination pixel coordinates in the second plurality of vectors in the third lookup table to obtain a second portion of the destination image data.
This invention relates to image processing techniques for transforming source image data into destination image data using lookup tables and remapping operations. The problem addressed involves efficiently generating high-quality transformed images while minimizing computational overhead. The method involves generating a first lookup table containing a first plurality of vectors, each vector mapping a source pixel coordinate to a destination pixel coordinate. A second lookup table is generated with a second plurality of vectors, each mapping a destination pixel coordinate to a source pixel coordinate. A third lookup table is created, where each entry corresponds to a destination pixel coordinate and contains a vector pointing to a source pixel coordinate. The method further includes applying a non-linear remapping operation from the source image data to each destination pixel coordinate in the second plurality of vectors within the third lookup table to obtain a second portion of the destination image data. This non-linear remapping allows for complex transformations, such as distortion correction or artistic effects, while maintaining computational efficiency. The use of multiple lookup tables ensures accurate and fast mapping between source and destination coordinates, enabling real-time or near-real-time image processing applications. The invention is particularly useful in fields requiring precise image transformations, such as medical imaging, computer vision, and graphics rendering.
8. The method of claim 7 , wherein the non-linear remapping operation comprises retrieving, by the computer processor and from the source image data, second source pixel data corresponding to a respective one of the second plurality of vectors in the third lookup table based on the pixel-to-pixel mapping in the first lookup table.
This invention relates to image processing techniques for non-linear remapping of pixel data. The method addresses the challenge of efficiently transforming source image data into a target representation while preserving visual quality and computational efficiency. The process involves generating a first lookup table that defines a pixel-to-pixel mapping between source and target images. A second lookup table is then created to store vectors representing non-linear transformations for specific pixels. During remapping, the system retrieves source pixel data corresponding to vectors in the second lookup table based on the mappings defined in the first lookup table. This approach allows for precise, non-linear adjustments to pixel values while minimizing computational overhead. The method ensures accurate remapping by leveraging precomputed mappings and vector-based transformations, making it suitable for applications requiring high-quality image processing with constrained resources. The technique is particularly useful in scenarios where real-time performance and visual fidelity are critical, such as in medical imaging, computer vision, or graphics rendering. The invention optimizes the remapping process by combining structured lookup tables with dynamic vector-based adjustments, enabling efficient handling of complex image transformations.
9. The method of claim 8 , further comprising performing, by the computer processor, an interpolation on the second source pixel data to obtain the second portion of the destination image data.
This invention relates to image processing, specifically methods for generating high-resolution images from lower-resolution source images. The problem addressed is the need to efficiently upscale images while maintaining visual quality, particularly when working with multiple source images that may have different resolutions or misalignments. The method involves processing at least two source images to produce a higher-resolution destination image. First, the source images are aligned to correct for any positional discrepancies. Then, the method extracts pixel data from the first source image to form a first portion of the destination image data. For the remaining portions of the destination image, the method performs an interpolation on pixel data from the second source image to generate the second portion of the destination image data. This interpolation step ensures smooth transitions and accurate representation of details in the upscaled image. The technique is particularly useful in applications where multiple source images must be combined, such as in medical imaging, satellite imagery, or multi-camera systems, where alignment and resolution differences can degrade output quality. By aligning the sources and selectively using interpolation, the method improves the fidelity of the final high-resolution image.
10. A computer program product comprising a non-transitory, computer-readable medium having instructions encoded thereon that when executed by one or more processors cause a process to be carried out, the process comprising: receiving a first lookup table representing a pixel-to-pixel mapping of source pixel coordinates of an input image to destination pixel coordinates of an output image; generating a second lookup table representing a vector-to-pixel mapping of a first plurality of vectors of the destination pixel coordinates to a first plurality of the source pixel coordinates based on the first lookup table; receiving source image data; and applying a linear remapping operation from the source image data to each of the destination pixel coordinates in the first plurality of vectors in the second lookup table to obtain a first portion of destination image data.
This invention relates to image processing, specifically to efficient pixel remapping for image transformation. The problem addressed is the computational cost of directly applying pixel-to-pixel mappings in image transformations, which can be inefficient for large images or complex transformations. The solution involves a two-step process. First, a first lookup table is received, defining a direct pixel-to-pixel mapping from source pixel coordinates in an input image to destination pixel coordinates in an output image. This table represents the desired transformation, such as warping, resizing, or perspective correction. Next, a second lookup table is generated, which optimizes the transformation by mapping vectors of destination pixels to corresponding source pixels. This second table groups destination pixels into vectors, allowing for batch processing. Source image data is then processed by applying a linear remapping operation using the second lookup table, which maps the source image data to the destination pixel coordinates defined in the vectors. This approach reduces computational overhead by leveraging vectorized operations instead of processing individual pixels. The method improves efficiency by minimizing redundant calculations and enabling parallel processing of pixel groups, making it suitable for real-time or high-resolution image transformations.
11. The computer program product of claim 10 , wherein all of the pixel-to-pixel mappings in the first lookup table are linear with slope 1 for all of the destination pixel coordinates in each of the first plurality of vectors.
This invention relates to image processing, specifically to a method for generating lookup tables that map source pixel coordinates to destination pixel coordinates in a transformed image. The problem addressed is the computational inefficiency and complexity of traditional image transformation techniques, which often require real-time calculations for each pixel during rendering. The solution involves precomputing and storing pixel-to-pixel mappings in lookup tables to accelerate the transformation process. The invention describes a computer program product that includes a first lookup table storing mappings between source and destination pixel coordinates for a first plurality of vectors. The key feature is that all pixel-to-pixel mappings in this lookup table are linear with a slope of 1 for all destination pixel coordinates in each of the first plurality of vectors. This linearity simplifies the interpolation process, ensuring that the transformation can be applied efficiently without complex calculations. The lookup table may be used in conjunction with other tables or interpolation methods to handle non-linear transformations or edge cases. The approach reduces computational overhead by leveraging precomputed mappings, making it suitable for real-time applications such as video processing or graphics rendering. The invention improves performance by minimizing runtime calculations while maintaining accuracy in the transformed output.
12. The computer program product of claim 10 , wherein the linear remapping operation comprises retrieving, from the source image data, first source pixel data corresponding to a respective one of the first plurality of vectors in the second lookup table based on the vector-to-pixel mapping in the second lookup table.
This invention relates to image processing, specifically techniques for remapping pixel data in images using vector-based lookup tables. The problem addressed involves efficiently transforming source image data into a target format while preserving visual quality, particularly when dealing with high-dimensional or complex image representations. The invention describes a method for performing a linear remapping operation on image data. A source image is processed by generating a first lookup table that maps vectors to pixel data in the source image. A second lookup table is created to map these vectors to corresponding pixel data in a target image. During the remapping operation, the system retrieves first source pixel data from the source image based on the vector-to-pixel mapping defined in the second lookup table. This allows for precise and efficient transformation of pixel values from the source to the target image while maintaining consistency in the image representation. The technique leverages vector-based mappings to streamline the remapping process, reducing computational overhead compared to traditional pixel-by-pixel transformations. The use of lookup tables ensures that the remapping operation is both accurate and scalable, making it suitable for applications requiring real-time or high-performance image processing. The invention is particularly useful in scenarios where image data must be converted between different formats or representations while minimizing distortion or loss of detail.
13. The computer program product of claim 12 , wherein the process further comprises performing an interpolation on the first source pixel data to obtain the first portion of the destination image data.
14. The computer program product of claim 10 , wherein the process further comprises generating a third lookup table representing a listing of a second plurality of vectors of the destination pixel coordinates.
The invention relates to computer graphics processing, specifically optimizing the rendering of images by efficiently managing pixel coordinate data. The problem addressed is the computational overhead in rendering systems when handling large datasets of pixel coordinates, particularly in tasks like image warping, texture mapping, or other transformations where pixel positions must be recalculated. The invention involves a computer program product that includes a process for generating and utilizing lookup tables to streamline pixel coordinate transformations. The process generates a first lookup table containing a plurality of vectors representing source pixel coordinates, which are then mapped to destination pixel coordinates. A second lookup table is created to store these destination coordinates, allowing for faster access and reducing redundant calculations. Additionally, the process generates a third lookup table that lists a second plurality of vectors of the destination pixel coordinates, further optimizing data retrieval and processing efficiency. This multi-table approach minimizes computational load by avoiding repeated calculations and enabling quick reference to precomputed coordinate values, thereby improving rendering performance in graphics applications. The system is particularly useful in real-time rendering environments where speed and efficiency are critical.
15. The computer program product of claim 14 , wherein any of the pixel-to-pixel mappings in the first lookup table are not linear with slope 1 for any of the destination pixel coordinates in each of the second plurality of vectors.
This invention relates to image processing, specifically to a computer program product that enhances image transformation by using non-linear pixel-to-pixel mappings in a lookup table. The problem addressed is the limitation of traditional linear transformations, which often fail to accurately represent complex image distortions or optimizations. The solution involves a first lookup table that stores non-linear mappings between source and destination pixel coordinates, where the mappings are not constrained to a slope of 1. These mappings are applied to a second plurality of vectors, which define the spatial relationships between pixels in the transformed image. The non-linear approach allows for more flexible and precise adjustments, such as correcting lens distortions, applying artistic effects, or optimizing image compression. The invention ensures that the mappings are not restricted to simple linear relationships, enabling more sophisticated and adaptive image processing techniques. The computer program product executes these transformations efficiently, improving the quality and accuracy of the output image.
16. The computer program product of claim 14 , wherein the process further comprises applying a non-linear remapping operation from the source image data to each of the destination pixel coordinates in the second plurality of vectors in the third lookup table to obtain a second portion of the destination image data.
This invention relates to image processing, specifically techniques for transforming source image data into destination image data using lookup tables and remapping operations. The problem addressed involves efficiently generating high-quality destination images from source images by leveraging precomputed lookup tables and optimized remapping processes. The system involves generating a first lookup table containing a first plurality of vectors, each vector representing a mapping from source pixel coordinates to destination pixel coordinates. A second lookup table is generated containing a second plurality of vectors, each representing a mapping from destination pixel coordinates to source pixel coordinates. A third lookup table is generated containing a third plurality of vectors, each representing a mapping from source pixel coordinates to destination pixel coordinates. The process includes applying a linear remapping operation from the source image data to each of the destination pixel coordinates in the first plurality of vectors in the first lookup table to obtain a first portion of the destination image data. Additionally, a non-linear remapping operation is applied from the source image data to each of the destination pixel coordinates in the second plurality of vectors in the third lookup table to obtain a second portion of the destination image data. This approach allows for efficient and accurate image transformations by combining linear and non-linear remapping techniques, improving computational efficiency and image quality.
17. The computer program product of claim 16 , wherein the non-linear remapping operation comprises retrieving, from the source image data, second source pixel data corresponding to a respective one of the second plurality of vectors in the third lookup table based on the pixel-to-pixel mapping in the first lookup table.
The software adjusts an image by looking up corresponding pixel locations in the original image based on a pixel mapping table, effectively warping the image in a non-linear way.
18. The computer program product of claim 17 , wherein the process further comprises performing, by the computer processor, an interpolation on the second source pixel data to obtain the second portion of the destination image data.
The invention relates to image processing, specifically to methods and systems for generating high-resolution images from lower-resolution source images. The problem addressed is the need to improve image quality when upscaling or interpolating images, particularly in scenarios where multiple source images are combined to form a higher-resolution destination image. The invention involves a computer program product that processes multiple source images to generate a destination image with improved resolution. The process includes selecting a first portion of destination image data from a first source image and a second portion of destination image data from a second source image. The second source image is aligned with the first source image to ensure proper registration. The invention further includes performing an interpolation on the second source pixel data to refine the second portion of the destination image data, enhancing the overall quality of the final image. This interpolation step helps smooth transitions and reduce artifacts that may arise from combining multiple source images. The method ensures that the destination image retains high fidelity by leveraging the best available data from each source image while minimizing distortions. The invention is particularly useful in applications such as medical imaging, satellite imaging, and digital photography, where high-resolution images are required from lower-resolution inputs.
19. A system comprising: a storage; one or more computer processors operatively coupled to the storage, the one or more computer processors configured to execute instructions stored in the storage that when executed cause any of the one or more computer processors to carry out a process comprising: receiving a first lookup table representing a pixel-to-pixel mapping of source pixel coordinates of an input image to destination pixel coordinates of an output image; generating a second lookup table representing a vector-to-pixel mapping of a first plurality of vectors of the destination pixel coordinates to a first plurality of the source pixel coordinates based on the first lookup table; receiving source image data; and applying a linear remapping operation from the source image data to each of the destination pixel coordinates in the first plurality of vectors in the second lookup table to obtain a first portion of destination image data.
This system addresses the challenge of efficiently transforming input images into output images with precise pixel mappings, particularly in applications requiring high-performance image processing, such as real-time rendering or medical imaging. The system includes a storage and one or more computer processors that execute instructions to perform image transformation. The process begins by receiving a first lookup table that defines a pixel-to-pixel mapping between source pixel coordinates of an input image and destination pixel coordinates of an output image. The system then generates a second lookup table, which maps vectors of destination pixel coordinates to corresponding source pixel coordinates based on the first lookup table. This second lookup table enables vector-based remapping, improving computational efficiency. The system receives source image data and applies a linear remapping operation to transform the source image data into destination image data, using the second lookup table to map vectors of destination coordinates to their corresponding source coordinates. This approach optimizes image transformation by leveraging vector-based mappings, reducing the computational overhead associated with traditional pixel-by-pixel remapping. The system is particularly useful in applications requiring fast, accurate image transformations, such as video processing, augmented reality, or medical imaging systems.
20. The system of claim 19 , wherein the linear remapping operation comprises retrieving, from the source image data, first source pixel data corresponding to a respective one of the first plurality of vectors in the second lookup table based on the vector-to-pixel mapping in the second lookup table.
This invention relates to image processing systems that perform linear remapping operations to transform source image data into target image data. The system addresses the challenge of efficiently mapping source pixels to target pixels in a computationally optimized manner, particularly for applications requiring high-speed image transformations such as real-time rendering or video processing. The system includes a first lookup table that stores a plurality of vectors, each representing a mapping between source pixels and target pixels. A second lookup table contains a vector-to-pixel mapping that associates each vector with corresponding source pixel data. During the linear remapping operation, the system retrieves first source pixel data from the source image data based on the vector-to-pixel mapping in the second lookup table. This allows the system to quickly access the necessary source pixel data for transformation without performing expensive computations for each pixel individually. The system further includes a processor configured to apply a linear transformation to the retrieved source pixel data using the vectors from the first lookup table, generating transformed pixel data. The transformed pixel data is then stored in a target image buffer, producing the final output image. This approach reduces computational overhead by leveraging precomputed mappings and efficient data retrieval, enabling faster image processing while maintaining accuracy. The system is particularly useful in applications where real-time performance is critical, such as augmented reality, medical imaging, or high-definition video streaming.
21. The system of claim 20 , wherein the process further comprises performing an interpolation on the first source pixel data to obtain the first portion of the destination image data.
The system relates to image processing, specifically to methods for generating high-resolution images from lower-resolution source images. The problem addressed is the need to accurately reconstruct or upscale images while preserving detail and minimizing artifacts. The system includes a process that performs interpolation on source pixel data to generate a portion of the destination image data. This interpolation step is used to estimate missing pixel values in the destination image, allowing for the creation of a higher-resolution output from lower-resolution input. The interpolation may involve techniques such as bilinear, bicubic, or more advanced methods to improve image quality. The system may also include additional steps, such as filtering or noise reduction, to enhance the final output. The interpolation process ensures that the destination image maintains smooth transitions and avoids distortions that can occur during simple scaling operations. The overall goal is to provide a computationally efficient yet effective way to produce high-quality, high-resolution images from lower-resolution source data.
22. The system of claim 19 , wherein the process further comprises generating a third lookup table representing a listing of a second plurality of vectors of the destination pixel coordinates.
A system for image processing generates a third lookup table containing a second set of vectors representing destination pixel coordinates. This system is part of a broader image processing framework that includes generating a first lookup table representing a first set of vectors of source pixel coordinates and a second lookup table representing a second set of vectors of source pixel coordinates. The system also includes a processor configured to perform a transformation process using the first and second lookup tables to map source pixel coordinates to destination pixel coordinates. The third lookup table, which lists the second set of vectors of destination pixel coordinates, is generated as part of this transformation process. This allows for efficient and accurate mapping of pixel data in image processing applications, such as image warping, resampling, or geometric transformations. The system ensures precise coordinate transformations by leveraging multiple lookup tables to handle different stages of the mapping process, improving computational efficiency and accuracy in image manipulation tasks.
23. The computer program product of claim 22 , wherein the process further comprises applying a non-linear remapping operation from the source image data to each of the destination pixel coordinates in the second plurality of vectors in the third lookup table to obtain a second portion of the destination image data.
This invention relates to image processing, specifically to techniques for transforming source image data into destination image data using lookup tables and remapping operations. The problem addressed involves efficiently generating high-quality image transformations, such as those required in graphics rendering, medical imaging, or computer vision, where traditional methods may suffer from computational inefficiency or quality degradation. The invention describes a method for generating destination image data from source image data using multiple lookup tables. A first lookup table maps source pixel coordinates to a first set of destination pixel coordinates, producing a first portion of the destination image data. A second lookup table maps source pixel coordinates to a second set of destination pixel coordinates, producing a second portion of the destination image data. A third lookup table applies a non-linear remapping operation to the source image data for each destination pixel coordinate in the second set, further refining the transformation. This multi-stage approach allows for precise control over the image transformation process, enabling complex mappings while maintaining computational efficiency. The technique is particularly useful in applications requiring high-fidelity image transformations, such as real-time rendering, medical imaging reconstruction, or image warping in augmented reality. By separating the transformation into distinct stages, the method ensures accuracy and flexibility in handling various types of image data.
24. The system of claim 23 , wherein the non-linear remapping operation comprises retrieving, from the source image data, second source pixel data corresponding to a respective one of the second plurality of vectors in the third lookup table based on the pixel-to-pixel mapping in the first lookup table.
This invention relates to image processing systems that perform non-linear remapping operations to transform source image data into target image data. The system addresses the challenge of efficiently and accurately mapping pixels from a source image to a target image while preserving visual quality, particularly when dealing with complex transformations that require non-linear adjustments. The system includes a first lookup table that defines a pixel-to-pixel mapping between source and target image data. A second lookup table stores a plurality of vectors, each representing a transformation direction for a corresponding pixel in the target image. A third lookup table contains a plurality of vectors that define a non-linear remapping operation. During processing, the system retrieves second source pixel data from the source image based on the pixel-to-pixel mapping in the first lookup table and the vectors in the third lookup table. This allows the system to apply non-linear transformations while maintaining precise control over pixel placement, improving image quality and reducing artifacts. The non-linear remapping operation ensures that pixels are accurately positioned in the target image according to the defined transformations, even when the mapping involves complex, non-linear adjustments. This approach enhances the flexibility and accuracy of image processing tasks, such as warping, distortion correction, or other geometric transformations. The use of multiple lookup tables optimizes performance by precomputing transformation vectors, reducing runtime computational overhead.
25. The system of claim 24 , wherein the process further comprising performing, by the computer processor, an interpolation on the second source pixel data to obtain the second portion of the destination image data.
This invention relates to image processing systems that enhance image quality by interpolating pixel data. The system addresses the challenge of accurately reconstructing high-resolution images from lower-resolution source data, particularly when scaling or resizing images. The system includes a computer processor configured to process source pixel data from multiple sources to generate destination image data. The processor performs interpolation on the second source pixel data to obtain a portion of the destination image data, ensuring smooth transitions and improved visual quality. The interpolation process may involve techniques such as bilinear or bicubic interpolation to estimate missing pixel values based on neighboring pixels. The system may also incorporate additional processing steps, such as filtering or noise reduction, to further refine the output image. By applying interpolation to the second source pixel data, the system ensures that the destination image maintains clarity and detail, even when derived from lower-resolution inputs. This approach is particularly useful in applications requiring high-quality image scaling, such as digital photography, medical imaging, and video processing. The system's ability to interpolate pixel data efficiently enhances its performance in real-time applications where rapid image processing is critical.
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January 16, 2018
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